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Optimization Approaches for Solving String Selection Problems

Optimization Approaches for Solving String Selection Problems provides an overview of optimization methods for a wide class of genomics-related problems in relation to the string selection problems. This class of problems addresses the recognition of similar characteristics or differences within bio...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Pappalardo, Elisa (Autor), Pardalos, Panos M. (Autor), Stracquadanio, Giovanni (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:SpringerBriefs in Optimization,
Temas:
Acceso en línea:Texto Completo

MARC

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505 0 |a 1. Biological Sequences -- 2. Strings: Theory, Properties and Applications -- 3. Mathematical Optimization -- 4. String Selection Problems. 
520 |a Optimization Approaches for Solving String Selection Problems provides an overview of optimization methods for a wide class of genomics-related problems in relation to the string selection problems. This class of problems addresses the recognition of similar characteristics or differences within biological sequences. Specifically, this book considers a large class of problems, ranging from the closest string and substring problems, to the farthest string and substring problems, to the far from most string problem. Each problem includes a detailed description, highlighting both biological and mathematical features and presents state-of-the-art approaches. This Brief provides a quick  introduction of optimization methods for string selection problems for young scientists and a detailed description of the mathematical and computational methods developed for experts in the field of optimization who want to deepen their understanding of the string selection problems. Researchers, practitioners and graduate students in the field of Computer Science, Operation Research, Mathematics, Computational Biology and Biomedicine will find this book useful. . 
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